45 research outputs found

    Unified Convergence Proofs of Continuous-Time Fictitious Play

    Full text link

    Cooperative Control and Potential Games

    Full text link

    Highly-parallelized simulation of a pixelated LArTPC on a GPU

    Get PDF
    The rapid development of general-purpose computing on graphics processing units (GPGPU) is allowing the implementation of highly-parallelized Monte Carlo simulation chains for particle physics experiments. This technique is particularly suitable for the simulation of a pixelated charge readout for time projection chambers, given the large number of channels that this technology employs. Here we present the first implementation of a full microphysical simulator of a liquid argon time projection chamber (LArTPC) equipped with light readout and pixelated charge readout, developed for the DUNE Near Detector. The software is implemented with an end-to-end set of GPU-optimized algorithms. The algorithms have been written in Python and translated into CUDA kernels using Numba, a just-in-time compiler for a subset of Python and NumPy instructions. The GPU implementation achieves a speed up of four orders of magnitude compared with the equivalent CPU version. The simulation of the current induced on 10^3 pixels takes around 1 ms on the GPU, compared with approximately 10 s on the CPU. The results of the simulation are compared against data from a pixel-readout LArTPC prototype

    Dynamic fictitious play, dynamic gradient play, and distributed convergence to Nash equilibria

    No full text

    A Decomposition Approach to Distributed Control of Spatially Invariant Systems

    No full text

    Set-valued observers and optimal disturbance rejection

    No full text

    Autopilot Design for a Square Cross-section Missile

    No full text

    Robust Gain Scheduling for Smart-Structures in Parallel Robots

    No full text
    Smart-structures offer the potential to increase the productivity of parallel robots by reducing disturbing vibrations caused by high dynamic loads. In parallel robots the vibration behavior of the structure is position dependent. A single robust controller is not able to gain satisfying control performance within the entire workspace. Hence, vibration behavior is linearized at several operating points and robust controllers are designed. Controllers can be smoothly switched by gain-scheduling. A stability proof for fast varying scheduling parameters based on the Small-Gain Theorem is developed. Experimental data from Triglide, a four degree of freedom (DOF) parallel robot of the Collaborative Research Center 562, validate the presented concepts
    corecore